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Parallel File Systems

In: Data Engineering

Author

Listed:
  • Robert Ross

    (Argonne National Laboratory)

  • Philip Carns

    (Argonne National Laboratory)

  • David Metheny

    (Acxiom Corporation Conway)

Abstract

The success of a CDI Grid is dependent upon the design of its storage infrastructure. As seen in Chapter 7, processing in this environment revolves around the simultaneous movement and transformation of data on many compute elements. Effective storage solutions combine hardware and software to meet these needs. The storage hardware selected must provide enough raw throughput for the expected workloads. Typical storage hardware architectures also often provide some redundancy to help in creating a fault tolerant system. Storage software, specifically file systems, must organize this storage hardware into a single logical space, provide efficient mechanisms for accessing that space, and hide common hardware failures from compute elements.

Suggested Citation

  • Robert Ross & Philip Carns & David Metheny, 2009. "Parallel File Systems," International Series in Operations Research & Management Science, in: Yupo Chan & John Talburt & Terry M. Talley (ed.), Data Engineering, chapter 8, pages 143-168, Springer.
    • Handle: RePEc:spr:isochp:978-1-4419-0176-7_8
    DOI: 10.1007/978-1-4419-0176-7_8
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    Cited by:

    1. Dawen Xia & Xiaonan Lu & Huaqing Li & Wendong Wang & Yantao Li & Zili Zhang, 2018. "A MapReduce-Based Parallel Frequent Pattern Growth Algorithm for Spatiotemporal Association Analysis of Mobile Trajectory Big Data," Complexity, Hindawi, vol. 2018, pages 1-16, January.
    2. Shaoming Pan & Yongkai Li & Zhengquan Xu & Yanwen Chong, 2015. "Distributed Storage Algorithm for Geospatial Image Data Based on Data Access Patterns," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-22, July.

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